An Intelligent System for Fresh Bitter Gourd Detection Using CNN

dc.contributor.authorTasnim, Zarin
dc.date.accessioned2021-12-08T08:45:11Z
dc.date.available2021-12-08T08:45:11Z
dc.date.issued2021-09-20
dc.description.abstractAgriculture development is not only a normal development sector but also a vital sector all over the world. Convolution Neural Network is one of the most advanced algorithms in Machine Learning. In my study, I have built up a strong relationship between agriculture and Image processing system, bitter gourd freshness detection and automation system using multi-layer automation process. I have used 5*3 training layers for the dataset and relevant output process. In this study, I show 4 types of output like Fresh, Moderate, Wrong and rotten bitter gourd. After analyzing data and method implementation I get 91.56% model accuracy which is better than the other image processing algorithm. In the modern era agriculture development is the highly contribute field of food security. This study will allow farmers to choose the proper crop in the right market condition, which will play a key role in strengthening the economy of the country. Technology on the other hand is a huge blessing in people's lives. In today's world, the introduction of information technology in agriculture has led to great improvements in this field.
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6539
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6539
dc.language.isoen_US
dc.publisherDaffodil International University
dc.sourceDIU Institutional Repository
dc.subjectSustainable agriculture
dc.subjectTechnology assessment
dc.titleAn Intelligent System for Fresh Bitter Gourd Detection Using CNN
dc.typeOther

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